Title :
Establishing work design criteria through a highest expected utility neural network model: An automotive trim case study
Author :
Quintana, Rolando ; Leun, Mark T.
Author_Institution :
Dept. of Manage. Sci. & Stat., Univ. of Texas at San Antonio, San Antonio, TX, USA
Abstract :
The purpose of this research is two-folded. First, it attempts to maximize productivity and yield as well as to minimize the spatial fixed cost through the development of a work design decision making tool for optimizing work cell configurations and ergonomics. Second, the case study applies influence diagram and neural network to analyze and evaluate work/process design criteria. Practically, the industrial problem is to compare the new stand-up sewing cells against the traditional sit-down sewing layout while taking into consideration of ergonomic effect (repetitive motion injury (RMI) likelihood), floor space (SF), yield (%), and cost ($). The work design decision making tool used in the current study is based on influence diagram run on the HUGIN neural network software. Statistical tests are used to benchmark and validate the experimental results and actual data. Findings suggest that neural network is an effective alternative in solving work design problem.
Keywords :
automotive components; cost reduction; ergonomics; neural nets; occupational safety; production engineering computing; productivity; statistical testing; HUGIN neural network software; automotive trim; ergonomics optimization; expected utility neural network model; floor space; industrial problem; influence diagram; process design criteria; productivity maximisation; repetitive motion injury likelihood; sit-down sewing layout; spatial fixed cost minimisation; stand-up sewing cells; statistical tests; work cell configuration optimization; work design criteria; work design decision making tool; Aerospace industry; Automotive engineering; Cost function; Decision making; Design optimization; Ergonomics; Neural networks; Process design; Productivity; Utility theory; Work design; ergonomics; neural network;
Conference_Titel :
Industrial Engineering and Engineering Management, 2008. IEEM 2008. IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-2629-4
Electronic_ISBN :
978-1-4244-2630-0
DOI :
10.1109/IEEM.2008.4738053